This is a Read Me document to keep track of all files uploaded.

- Analysis: The files used for Analysis

	- data
		- climate: folder that contains clean climate data
		- demographics: folder that contains clean demographics data
		- onion: folder that contains onion prices data
		- output_data: folder that contains the "final_onion_fixed.csv" dataset which is a clean dataset used for analysis
		- stone_pelt: folder that contains all the stone pelting datasets that were merged

	- Analysis.Rproj: The R Project file

	- Data_Replication.Rmd: R Markdown file that was used to merge all individual datasets into a dataset called "final_onion_fixed.csv" that was used for analysis.

	- descriptive_statistics_of_data.Rmd: R Markdown file that was used to generate descriptive statistics of the dataset used for analysis "final_onion_fixed.csv".

	- Figures.Rmd: R Markdown filed that was used to generate visualizations for the paper.

	- statistical_analysis_of_our_data.Rmd: R Markdown file used for statistical analysis.



- PDFs_Data: This folder contains the PDF's for pages from where data was pulled.

	- Demographics_Data_PDFs: PDF's of webpages from where demographic data was pulled from

	- MHA_Files: Official documentation on stone-pelting by the Government of India

	- Newspapers_PDFs: Folder with 4 sub-folders each containing the pdf of the news article of the newspaper
		- DailyExcelsior: 92 different news article PDF's
		- GreaterKashmir: 28 different news article PDF's 
		- KashmirObserver: 9 different news article PDF's
		- KashmirTimes: 72 different news article PDF's

	- Onion_Price_PDF: PDF's of Onion Price details from website (first and last page of data)

	- Ramadan_Dates_PDFs: PDF's of Ramadan Dates

	- SATP_Website_PDFs: SATP data PDF's



- Raw_Datasets: This folder contains all the raw datasets that were created/downloaded to merge for analysis

	- ACLED: ACLED Dataset and Codebook (ACLED, (2019). “Armed Conflict Location & Event Data Project (ACLED) Codebook.”)

	- Climate: Individually scraped time-series climate data csv files, scrapy.py, dataset_cleaner.ipynb
		- scrapy.py: Python file to scrape district-wise time-series climate data using API
		- dataset_cleaner.ipynb: Jupyter notebook used to merge all datasets into one.

	- Stone_Pelting_Newspapers: Folder with stone-pelting data logged using newspaper articles

	- Stone_Pelting_SATP
		- satp_raw_data.csv: Raw data scraped from SATP (South Asia Terrorism Portal) website
		- stone_pelting_cleaner.ipynb: Jupyter notebook file to clean raw data
		- satp_cleaned_data.csv: Cleaned SATP data